Timed fingerprint locating for idle-state user equipment in wireless networks

ABSTRACT

A user equipment (UE) location in a wireless network can be determined by leveraging geometric calculations for an overlaid bin grid framework mapping the wireless network area to store differential values for each frame of the bin grid framework for each pair of relevant NodeBs. A timing offset can be determined, such that when a time value from a target UE is accessed, the location can be quickly determined with minimal real time computation. In an aspect, the time value from an idle-state target UE can be accessed. The target UE time value can be searched among pre-computed differential value data sets indexed by relevant NodeB site pairs to return sets of frames that can facilitate converging on a location for the target UE. Intersecting frames can represent the geographic location of the UE in the wireless network. Further, the data can be leveraged to correct timing in the network.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.12/836,471, filed Jul. 14, 2010, which is a continuation-in-part of U.S.patent application Ser. No. 12/712,424, filed Feb. 25, 2010, both ofwhich are hereby incorporated by reference in their entireties.

TECHNICAL FIELD

The subject disclosure relates to wireless communications and, moreparticularly, to location determinations of mobile equipment in awireless network environment.

BACKGROUND

In mobile equipment networks, locating user equipments (UEs) can providevaluable additional benefits to users and opportunities for additionalor improved services. Typical mobile equipment networks provide wirelessaccess to various communications services for UEs, such as voice, video,data, messaging, content broadcast, VoIP, etc. Wireless networks typescan include Universal Mobile Telecommunications System (UMTS), Long TermEvolution (LTE), High Speed Packet Access (HSPA), Code Division MultipleAccess (CDMA), Time Division Multiple Access (TDMA), Frequency DivisionMultiple Access (FDMA), Multi-Carrier Code Division Multiple Access(MC-CDMA), Single-Carrier Code Division Multiple Access (SC-CDMA),Orthogonal frequency division multiple access (OFDMA), Single-carrierFDMA (SC-FDMA), etc.

Locating UEs in a wireless network can facilitate providinglocation-centric services or information in relation to the UE, such asE911 services, mapping services, or traffic information services, amongmany others. Additionally, UE location information can be employed toimprove network performance, to troubleshoot networks, by lawenforcement, to aggregate valuable demographic information, or nearly alimitless number of other uses. Such additional usage of UE locationdata can proactively include removal or obfuscation of identifyinginformation at various levels to address privacy concerns.

Traditional methods of determining UE locations include measuring thetiming delay of the signals transmitted between the wireless basestation and the wireless handset and applying various location servicesor methods, including, but not limited to, cell global identity andtiming advance (CGI+TA), CGI and round trip time (CGI+RTT), time ofarrival (TOA), or other custom methods. Network timing delays includesite timing delay in the wireless signal path among radio component(s)at the wireless base station and a sector antenna. Network timing delaysfurther include delays that can arise from various mismatches (e.g.,impedance mismatch) among electronic elements and components, straycapacitances and inductances, length of the antenna(s) cable(s) in basestation(s); tower height of base station, signal path scattering, or“signal bounces,” such as multipath or strong reflections, and the like.Propagation delay between a UE and a NodeB is conventionally assumed tobe negligible with respect to timing delay. However, depending on thearchitecture of the serving base station and covered sector antenna(s)signal propagation delay can be substantive, particularly in distributedantenna systems and low-power wireless radio cells and cause significanterror in UE location determinations for traditional methods.

It is becoming more common to try to determine propagation delay withimproved accuracy so as to improve UE location calculations.Conventional UE location techniques include, but are not limited to,Cell ID (CID) wherein errors of multiple km are expected, Enhanced CID(ECID) which includes mobile timing advance and allows location of themobile within an arc some distance from the base site and errors canstill be multiple km, RF signal strength (RSSI) reported by the UE oftenhaving errors of >1 km due to RSSI variation, Round Trip Time (RTT) formultilateration from three or more base sites with errors often >1 km,Uplink Time Difference of Arrival (UTDOA) using specialized receivers onthree or more base stations to measure the propagation time differencebetween the mobile and sites, or Assisted GPS (AGPS) using a GPSreceiver in a UE to compute its own location to <10 m where satellitecoverage is accessible (which can be <70% of the time.)

SUMMARY

The following presents a simplified summary of the disclosed subjectmatter in order to provide a basic understanding of some aspects of thedisclosed subject matter. This summary is not an extensive overview ofthe subject disclosure. It is intended to neither identify key orcritical elements of the subject disclosure nor delineate the scope ofthe disclosed subject matter. Its sole purpose is to present someconcepts of the disclosed subject matter in a simplified form as aprelude to the more detailed description that is presented later.

In an embodiment, a mobile device can include a memory storingcomputer-executable instructions and a processor that facilitatesexecution of the computer-executable instructions. These instructionscan cause the processor to receive an observed time value associatedwith wireless cellular radio links between a pair of radios and a UE.The user equipment can be powered on but not in an active call session.The processor can further determine a differential time value based onthe observed time value, a reference observed time value, and areference differential time value.

In a further embodiment, a method can include receiving, by a system, atime value associated with radio links between a pair of radios and aUE. The user equipment can be in an idle-state. Further, the method caninclude determining, by the system, a differential time value based onthe observed time value, a reference observed time value, and areference differential time value.

In another embodiment, a system can include a processor and memory. Theprocessor can facilitate the execution of computer-executableinstructions stored on the memory. The execution of thecomputer-executable instructions can cause the processor to receive anobserved time value associated with synchronization of radio linksbetween a pair of radios of a wireless network and a UE. The UE can bein an idle-mode. The processor can further determine a differential timevalue based on the observed time value, a reference observed time value,and a reference differential time value. The reference observed timevalue and reference differential time value can be predetermined.

To the accomplishment of the foregoing and related ends, the disclosedsubject matter, then, comprises the features hereinafter fullydescribed. The following description and the annexed drawings set forthin detail certain illustrative aspects of the disclosed subject matter.However, these aspects are indicative of but a few of the various waysin which the principles of the disclosed subject matter may be employed.Other aspects, advantages and novel features of the disclosed subjectmatter will become apparent from the following detailed description ofthe disclosed subject matter when considered in conjunction with thedrawings.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 illustrates a schematic exemplary wireless environment that canoperate in accordance with aspects of the disclosed subject matter.

FIG. 2 is a diagram of a subset of wireless devices (UEs) in a timefingerprint location wireless environment, in accordance with aspects ofthe disclosed subject matter.

FIG. 3 is a diagram illustrating differential propagation delay sets forNBSPs in a time fingerprint location wireless environment in accordancewith aspects described herein.

FIG. 4 is a block diagram of an exemplary system that facilitatescalibration of wireless signal propagation delay in accordance withaspects described herein.

FIG. 5 is a diagram depicting additional or alternative timing and/orlocation data generation components facilitate calibration of referenceframes in accordance with aspects described herein.

FIG. 6 presents a flowchart of an exemplary method for determining alocation for a UE.

FIG. 7 is a flowchart of an exemplary method for iteratively determininga location of a UE in a TFL wireless network according to aspects of thedisclosed subject matter

FIG. 8 presents a flowchart of an exemplary method for updating sitetiming values according to aspects of the disclosed subject matterdescribed herein.

FIG. 9 illustrates a block diagram of an exemplary embodiment of anaccess point to implement and exploit one or more features or aspects ofthe disclosed subject matter.

FIG. 10 is a block diagram of an exemplary embodiment of a mobilenetwork platform to implement and exploit various features or aspects ofthe disclosed subject matter.

DETAILED DESCRIPTION

The disclosed subject matter is now described with reference to thedrawings, wherein like reference numerals are used to refer to likeelements throughout. In the following description, for purposes ofexplanation, numerous specific details are set forth in order to providea thorough understanding of the disclosed subject matter. It may beevident, however, that the disclosed subject matter may be practicedwithout these specific details. In other instances, well-knownstructures and devices are shown in block diagram form in order tofacilitate describing the disclosed subject matter.

One or more embodiments of the disclosed subject matter providessystem(s) or method(s) for determining the location(s) of UE(s) in awireless network. In a particular aspect of the disclosed subjectmatter, location of UEs can be determined even when the UEs are in “idlemode” (e.g., are in an idle-state, standby state, not being activelyemployed by a user for communications, etc.) These system(s) ormethod(s) can facilitate determinations of propagation delay values ofwireless signals that can be leveraged to improve network performance,e.g., to allow for correction of wireless network system timing.Further, location determinations can facilitate location-centricservices and information related to the UE (e.g., mapping, points ofinterest, etc.) and/or by other entities (e.g., E911, traffic analysis,population demographics, etc.) Location determinations from anidle-state can be used in lieu of, to augment, to supplement, or tocompliment, location determinations made in an active state.

Wireless signals can be radio frequency signals, microwave signals, orother electromagnetic waves employed for telecommunication. Compensationof signal path propagation can be accomplished for sources of delay,such as, for example, mismatches (e.g., impedance mismatch) amongelectronic elements and components, stray capacitances and inductances,length of the antenna(s) cable(s) in base station(s); tower height ofbase station, signal propagation scattering, or “signal bounces,” suchas multipath or strong reflections, etc. Signal path compensation iseffected, at least in part, through determination of a propagationdelay. Such determination is based, at least in part, on statisticalanalysis of the location of UEs (or other reference locations)throughout a coverage sector or cell. These UE locations can begenerated through time fingerprint locating (TFL) measurements ofwireless signals. In an aspect, high-accuracy (e.g., 1 m-10 m) locationestimates of select mobile devices, such as estimates obtained by way ofassisted global positioning system (AGPS) or other global navigationsatellite systems (GNSSs), e.g., Galileo or GLONNAS, can be leveraged inlocating UEs.

Aspects, features, or advantages of the various embodiments of thesubject disclosure can be exploited in wireless telecommunicationdevices, systems or networks. Non-limiting examples of such devices ornetworks include Femto-cell technology, Wi-Fi, WorldwideInteroperability for Microwave Access (WiMAX); Enhanced General PacketRadio Service (Enhanced GPRS); Third Generation Partnership Project(3GPP) Long Term Evolution (LTE); 3GPP UMTS; Third GenerationPartnership Project 2 (3GPP2) Ultra Mobile Broadband (UMB); High SpeedPacket Access (HSPA); High Speed Downlink Packet Access (HSDPA); HighSpeed Uplink Packet Access (HSUPA); GSM Enhanced Data Rate for GSMEvolution (EDGE) Radio Access Network (RAN) or GERAN; UMTS TerrestrialRadio Access Network (UTRAN); or LTE Advanced. Additionally, aspects ofthe disclosed subject matter can include legacy telecommunicationtechnologies.

As used in this application, the terms “component,” “system,”“platform,” “layer,” “selector,” “interface,” and the like are intendedto refer to a computer-related entity or an entity related to anoperational apparatus with one or more specific functionalities, whereinthe entity can be either hardware, a combination of hardware andsoftware, software, or software in execution. As an example, a componentmay be, but is not limited to being, a process running on a processor, aprocessor, an object, an executable, a thread of execution, a program,and/or a computer. By way of illustration, both an application runningon a server and the server can be a component. One or more componentsmay reside within a process and/or thread of execution and a componentmay be localized on one computer and/or distributed between two or morecomputers. Also, these components can execute from various computerreadable media having various data structures stored thereon. Thecomponents may communicate via local and/or remote processes such as inaccordance with a signal having one or more data packets (e.g., datafrom one component interacting with another component in a local system,distributed system, and/or across a network such as the Internet withother systems via the signal). As another example, a component can be anapparatus with specific functionality provided by mechanical partsoperated by electric or electronic circuitry, which is operated by asoftware or firmware application executed by a processor, wherein theprocessor can be internal or external to the apparatus and executes atleast a part of the software or firmware application. As yet anotherexample, a component can be an apparatus that provides specificfunctionality through electronic components without mechanical parts,the electronic components can include a processor therein to executesoftware or firmware that confers at least in part the functionality ofthe electronic components.

In addition, the term “or” is intended to mean an inclusive “or” ratherthan an exclusive “or.” That is, unless specified otherwise, or clearfrom context, “X employs A or B” is intended to mean any of the naturalinclusive permutations. That is, if X employs A; X employs B; or Xemploys both A and B, then “X employs A or B” is satisfied under any ofthe foregoing instances. Moreover, articles “a” and “an” as used in thesubject specification and annexed drawings should generally be construedto mean “one or more” unless specified otherwise or clear from contextto be directed to a singular form.

Moreover, terms like “user equipment (UE),” “mobile station,” “mobile,”subscriber station,” “subscriber equipment,” “access terminal,”“terminal,” “handset,” and similar terminology, refer to a wirelessdevice utilized by a subscriber or user of a wireless communicationservice to receive or convey data, control, voice, video, sound, gaming,or substantially any data-stream or signaling-stream. The foregoingterms are utilized interchangeably in the subject specification andrelated drawings. Likewise, the terms “access point (AP),” “basestation,” “Node B,” “evolved Node B (eNode B),” “home Node B (HNB),”“home access point (HAP),” and the like, are utilized interchangeably inthe subject application, and refer to a wireless network component orappliance that serves and receives data, control, voice, video, sound,gaming, or substantially any data-stream or signaling-stream from a setof subscriber stations. Data and signaling streams can be packetized orframe-based flows.

Furthermore, the terms “user,” “subscriber,” “customer,” “consumer,”“prosumer,” “agent,” and the like are employed interchangeablythroughout the subject specification, unless context warrants particulardistinction(s) among the terms. It should be appreciated that such termscan refer to human entities or automated components supported throughartificial intelligence (e.g., a capacity to make inference based oncomplex mathematical formalisms) which can provide simulated vision,sound recognition and so forth.

The following abbreviations are relevant, at least in part, to thesubject specification.

-   3G Third Generation-   3GPP Third Generation Partnership Project-   AGPS Assisted GPS-   AP Access Point-   BCH Broadcast Channel-   CGI Cell Global Identity-   CN Core Network-   CS Circuit-Switched-   DAS Distributed Antenna System-   DCH Dedicated Transport Channel-   DSL Digital Subscriber Line-   E911 Enhanced 911-   FACH Forward Access Channel-   FL Forward Link-   GGSN Gateway GPRS Service Node-   GPRS General Packet Radio Service-   GSM Global System for Mobile Communication-   GNSS Global Navigation Satellite System-   GW Gateway-   ISDN Integrated Services Digital Network-   UE User Equipment-   IMS IP Multimedia Subsystem-   IP Internet Protocol-   ISP Internet Service Provider-   IPTV IP Television-   NBSP NodeB Site Pair-   PCH Paging Channel-   PCS Personal Communications Service-   PS Packet-Switched-   PSTN Public Switched Telephone Network-   RAN Radio Access Network-   RAT Radio Access Technology-   RBS Radio Base Station-   RL Reverse Link-   RL-TDOA RL Time Difference of Arrival-   RL-TOA RL Time of Arrival-   RNC Radio Network Controller-   RRC Radio Resource Control-   RTT Round Trip Time-   SGSN Serving GPRS Support Node-   TA Timing Advance-   U-TDOA Uplink Time Difference of Arrival-   U-TOA Uplink Time of Arrival-   URA UTRAN Registration Area-   UTRAN Universal Terrestrial Radio Access Network

FIG. 1 is a schematic of an exemplary wireless environment 100 that canoperate in accordance with aspects described herein. In particular,exemplary wireless environment 100 illustrates a set of wireless networkmacro cells. Three coverage macro cells 105 ₁-105 ₃ comprise theillustrative wireless environment; however, it should be appreciatedthat wireless cellular network deployments can encompass any number ofmacro cells, for example, 10⁴-10⁵ coverage macro cells. Coverage macrocells 105 _(λ) (λ=1,2,3) are illustrated as hexagons; however, coveragecells can adopt other geometries generally dictated by a deploymentconfiguration or floor plan, geographic areas to be covered, and so on.Each macro cell 105 _(λ) is sectorized in a 2π/3 configuration in whicheach macro cells includes three sectors, demarcated with dashed lines inFIG. 1. It should be appreciated that other sectorizations are possible,and aspects or features of the disclosed subject matter can be exploitedregardless of type of sectorization. Macro cells 105 ₁, 105 ₂, and 105 ₃are served respectively through NodeB 110 ₁, 110 ₂ and 110 ₃. Any twoNodeBs can be considered a NodeB site pair (NBSP) It is noted that radiocomponent(s) are functionally coupled through links such as cables(e.g., RF and microwave coaxial lines), ports, switches, connectors, andthe like, to a set of one or more antennas that transmit and receivewireless signals (not illustrated). It is noted that a radio networkcontroller (not shown), which can be a part of mobile networkplatform(s) 108, and set of base stations (e.g., Node B 110 _(n), withn=1, 2, . . . ) that serve a set of macro cells; electronic circuitry orcomponents associated with the base stations in the set of basestations; a set of respective wireless links (e.g., links 115 _(k) wherek=1, 2, . . . ) operated in accordance to a radio technology through thebase stations, form a macro radio access network (RAN). It is furthernoted, that based on network features, the radio controller can bedistributed among the set of base stations or associated radioequipment. In an aspect, for UMTS-based networks, wireless links 115_(λ) embody a Uu interface (UMTS Air Interface).

Mobile network platform(s) 108 facilitates circuit switched (CS)-based(e.g., voice and data) and packet-switched (PS) (e.g., internet protocol(IP), frame relay, or asynchronous transfer mode (ATM)) traffic andsignaling generation, as well as delivery and reception for networkedtelecommunication, in accordance with various radio technologies fordisparate markets. Telecommunication is based at least in part onstandardized protocols for communication determined by a radiotechnology utilized for communication. In addition telecommunication canexploit various frequency bands, or carriers, which include any EMfrequency bands licensed by the service provider (e.g., personalcommunication services (PCS), advanced wireless services (AWS), generalwireless communications service (GWCS), and so forth), and anyunlicensed frequency bands currently available for telecommunication(e.g., the 2.4 GHz industrial, medical and scientific (IMS) band or oneor more of the 5 GHz set of bands). In addition, wireless networkplatform(s) 108 can control and manage base stations 110 _(λ), and radiocomponent(s) associated thereof, in disparate macro cells 105 _(λ) byway of, for example, a wireless network management component (e.g.,radio network controller(s), cellular gateway node(s), etc.) Moreover,wireless network platform(s) can integrate disparate networks (e.g.,femto network(s), Wi-Fi network(s), femto cell network(s), broadbandnetwork(s), service network(s), enterprise network(s), . . . ) Incellular wireless technologies (e.g., 3rd Generation Partnership Project(3GPP) Universal Mobile Telecommunication System (UMTS), Global Systemfor Mobile Communication (GSM)), wireless network platform 108 isembodied in a core network and a set of radio network controllers.

In addition, wireless backhaul link(s) 151 can include wired linkcomponents like T1/E1 phone line; a digital subscriber line (DSL) eithersynchronous or asynchronous; an asymmetric DSL (ADSL); an optical fiberbackbone; a coaxial cable, etc.; and wireless link components such asline-of-sight (LOS) or non-LOS links which can include terrestrialair-interfaces or deep space links (e.g., satellite communication linksfor navigation). In an aspect, for UMTS-based networks, wirelessbackhaul link(s) 151 embodies IuB interface.

It should be appreciated that while exemplary wireless environment 100is illustrated for macro cells and macro base stations, aspects,features and advantages of the disclosed subject matter can beimplemented in microcells, picocells, femto cells, or the like, whereinbase stations are embodied in home-based access points.

Timing of wireless signals must take into consideration the time fromwave signal generation or output at radio equipment a transmitter (e.g.,a UE or NodeB) to detection at a receiver (e.g., a UE or NodeB). Suchtiming includes site timing through link(s) to antenna(s) andpropagation time over the air interface or wireless channel. Timingdelay typically is caused by various sources, e.g., mismatches amongelectronic elements and components (e.g., impedance mismatch), straycapacitances and inductances, length of the antenna(s) cable(s) in basestation(s); tower height of base station, whereas timing delay spreadgenerally originates from any signal path scattering, or “signalbounces,” such as multipath, strong reflections, etc.; and the like. Inan aspect of the disclosed subject matter, timing and delay errors canbe compensated for where the errors in delay and timing can bedetermined. Wherein better location measurements beget better timingmeasurements, aspects of the disclosed subject matter can, at least inpart, contribute to improved network performance. Similarly, bettertiming measurements can be employed for better location determination.Further, it is noted that compensation of timing delay can depend onsector coverage, e.g., a first sector can be densely populated (moreUEs) while a neighboring sector can include substantial areas of lowerpopulation density (fewer UEs).

A UE observed time difference, ‘C’, includes both a cell site timingportion, ‘A’, and a RF propagation portion, ‘B’, such that A+B=C.Further, where cell site location and UE location are known, the RFpropagation time, ‘B’, can be deduced, e.g., ‘B’=(distance between UEand cell site/speed of light). Using the deduced RF propagation time,‘B’, and Observed UE time difference, ‘C’, the cell site timing, ‘A’,can be calculated, as A=C−B. Site timing, ‘A’, is relatively stable overperiods of hours to days for most modern network equipment. Once ‘A’ isdetermined, ‘C’ can be measured for additional UEs and the RFpropagation time (i.e., ‘B’) for theses additional UEs can be determinedby B=C−A. RF propagation time, ‘B’, can then be converted into adistance (e.g., B*speed of light=distance) and, using multilaterationtechniques, UEs positions can be identified.

Determining the values of ‘B’ by geometry can be facilitated by having aknowledge of the location the NodeB and UE. NodeB locations aretypically known with high levels of precision, as these are normallypermanent installations. Further, the location of a first particular UEcan be determined using internal GPS systems (e.g., AGPS, usually towithin 5-10 meter accuracy). Thus an AGPS enabled UE can facilitate thedetermination of ‘A’, as disclosed herein, such that the location ofnon-location aware UEs in a macro cell can be calculated (e.g., bydetermining the subsequent ‘B’ for each measured ‘C’ and computing aposition, for example, by multilateration). In a particular aspect ofthe disclosed subject matter, location of UEs can be determined evenwhen the UEs are in “idle mode” (e.g., are in an idle-state, standbystate, not being actively employed by a user for communications, etc.)In experiments, computed ‘B’ values from measured ‘C’ values (e.g.,after an ‘A’ value has been determined using a location aware UE, asdisclosed herein) can produce location accuracies for non-location awareUEs with median errors of <70 m in suburban areas. Multilaterationincorporates compounding errors. Further, multilateration is alsocomputationally significant (e.g., involves hyperbolic functions betweenNBSPs at (N−1)!, where N is the number of cell sites, for example, 5cell sites would involve 24 simultaneous hyperbolic functions.) Timedfingerprint locating (TFL) and TFL for idle-state UEs, as disclosedherein, can reduce computational complexity and provide pre-computedvalues in lookup tables to further facilitate improved locationtechniques.

FIG. 2 is a diagram of a subset of wireless devices (e.g., UEs) in atimed fingerprint location (TFL) wireless environment 200, in accordancewith aspects of the disclosed subject matter. TFL wireless environment200 includes a bin grid 210 that is a relative coordinate frameworkwhich defines a matrix of evenly spaced points referred tointerchangeably as bins or frames. The frames can be correlated to ageographic data set, e.g., the bin grid 210 can provide identifiableregions of a predetermined area related to a mapping of a cell site,NodeB, county, country, etc. It can generally be stated that any UE isin one bin grid 210 frame at a given time.

Bin grid 210 frames can be of arbitrary size and/or number. As such, alllevels of frame granularity with regard to TFL techniques are consideredwithin the scope of the present disclosure. However, for simplicity, bingrid 210 (and also 310) frame size will be considered to be 100 metersby 100 meters for the purposes of discussion herein, as this closelymatches current UMTS chip size (e.g., UMTS chip rate is 3.84 MBit/sec,therefore one chip is roughly 260.42 nsec and 78 meters). Additionally,a bin grid can comprise other bin grids or portions thereof. Moreover,bin grids may overlap wholly or partially and at any orientation. Forsimplicity, only single bin grids are discussed herein, but allpermutations are considered within the scope of the present disclosure.It is further noted that a bin grid can be physically two dimensional(2D) or three dimensional (3D), wherein a 2D grid can, for example,include x,y coordinates (e.g., latitude, longitude) and a 3D grid canadd, for example, a z dimension (e.g., height). For simplicity, only 2Dbin grids are discussed herein, although both 2D and 3D bin grids areconsidered within the scope of this disclosure. Moreover, abstractdimensions can be considered, such as, for example, time, network type,subscriber level, etc. All such additional abstract dimensions arewithin the scope of the subject disclosure. For simplicity, theseadditional abstract dimensions will not be further discussed.

TFL wireless environment 200 can further include one or more NodeB cellbase sites 220, 222, 224. These NodeB are typically fixed locations withwell-characterized location coordinates such that the distance between aNodeB and any given frame of bin grid 210 can be easily computed. InFIG. 2, distances 230 and 232 correlate to measurements between NodeB220 and frames 250 and 254 respectively. Similarly, distances 234 and236 correlate to measurements between NodeB 222 and frames 250 and 254respectively. Likewise, distances 238 and 240 correlate to measurementsbetween NodeB 224 and frames 250 and 254 respectively. Given that thedistances from any NodeB to any frame in bin grid 210 can be accuratelycalculated because of the fixed geometry, the differential distance ofany frame to any two NodeB can similarly be accurately determined.Likewise, the distance between any two frames of bin grid 210 is readilycalculated because of a known geometry.

Additionally, TFL wireless environment 200 can include one or more UEs(e.g., mobile phones 260, 262, 264 and 266). These UEs can includelocation aware UEs (e.g., AGPS enabled UE) and non-location aware UEs.Wireless interactions with UEs can be correlated to nodes in bin grid210. For example, an AGPS enabled UE can determine a latitude andlongitude that can be correlated with a bin grid 210 node encompassingthat same latitude and longitude.

Where UE 260 is a location aware UE (e.g., UE 260 is AGPS enabled), UE260 can make location information available to the TFL wirelessenvironment 200, for example, through one or more NodeBs (e.g., 220,222, 224). UE 260, for instance, can be located at a latitude andlongitude within frame 250 of bin grid 210 and, for example, cantransmit this latitude and longitude location information, which can bereceived by, for example, NodeB 220. This latitude and longitudelocation information can be directly correlated to frame 250 and alsowith the RF propagation delay, ‘B’, to frame 250 from some NodeB in TFLwireless environment 200. For example, where UE 260 is located in frame250, propagation delay ‘B’ is closely approximated by the distance 230between NodeB 220 and UE 260 (located in frame 250) divided by the speedof light. Thus, the propagation delay ‘B’ can be directly determinedbecause the location of both the NodeB and the UE are known, asdisclosed herein. Further, NodeB 220 can communicate this locationinformation, propagation delay information, or derivatives thereof, toother equipment associated with the wireless network.

Given that the propagation delay, ‘B’, can be determined for locationaware UEs within TFL wireless environment 200, cell site delay, ‘A’, canbe determined where the observed UE time difference, ‘C’, is alsoavailable. Continuing the present example, UE 260 can make time data(e.g., a UE observed time difference, ‘C’) accessible to the TFLwireless environment 200. This observed time difference (OTD) can bemeasured for an active-state UE (e.g., a CFN-SFN OTD measurement, etc.).Further, in particular aspects of the subject disclosure, the OTD can bemeasured for an idle-state UE (e.g., a SFN-SFN OTD measurement, etc.) aswill be further disclosed herein. Continuing, cell site delay (‘A’) canbe calculated by subtracting the propagation delay (‘B’) from the UEobserved time difference (‘C’), e.g., A=C−B. As discussed herein, ‘A’ isgenerally stable over periods of hours to days. Assuming ‘A’ isrelatively stable, ‘B’ can be determined for some ‘C’ value (e.g.,B=C−A). Most or all UEs (e.g., both location enabled and non-locationenabled UEs) can make time data (e.g., an observed UE time difference,‘C’) available to the TFL wireless environment 200, for example bytransmitting it wirelessly (e.g., related to a SIB11 or SIB12 messagefor the 3GPP standard, etc.), such that the propagation delay for mostor all UEs can be determined with a simple calculation, given thedetermined ‘A’ value. Further, given that the propagation delay, ‘B’, isessentially proportional to distance (e.g., B*speed of light=distance),the propagation delay can be employed to map out a region of probablelocations for a UE at a set distance from the related NodeB (e.g., theNodeB from which the propagation delay was measured). This provides acentroid region in which the UE would likely be located.

It is well understood that errors can be associated with the variousmeasurements involved in the disclosed calculations, for example, AGPSmeasurements are only accurate to about 5-10 meters, an AGPS measurementcan be taken from various positions with a single 100 m×100 m bin gridframe, signals can be bounced, etc.) These errors can be addressed bywell-known statistical methods for sufficiently large sets of locationdata. In an aspect of the disclosed subject matter, a frame of bin grid210 can be selected as a reference frame and measurements within thatframe can be statistically manipulated to improve the value of the datagathered. For example, where UE 260 and UE 262 are both location awareUEs located within 250, the AGPS and time data from both UE s (260 and262) can be statistically combined and manipulated to increase therelevance of the collected data and the resulting calculated values.Moreover, measurements taken from other frames can be translated to thereference frame to facilitate an increased population of location datato improve statistical data correction processes. This translation canbe accomplished because knowledge of the spatial relationship betweenthe measured frame and reference frame is known. For example, UE 264 cantransmit AGPS location and time data from frame 252. This informationcan be accessed by a NodeB of TFL wireless environment 200. The data canbe manipulated to translate the measured data from frame 252 into theexpected values for UE 264 in frame 250. This can allow the AGPSlocation and time data, collected in various frames of bin grid 210 fromlocation aware UEs, to be correlated to a relevant reference frame. Thisinformation can then be statistically adapted to provide improved datafor use in calculating locations for non-location aware UEs. Theequations for translation among frames will be further disclosed herein.

Differential measurements can be computed for one or more frames of bingrid 210 for any plurality (e.g., pair) of NodeBs within TFL wirelessenvironment 200. For ease of understanding, bin grid 200 can comprise alarge plurality of frames that are each uniquely identified allowing asingle frame to be referenced by a “frame number”. Alternative frameidentification schemes are just as easily applied to identification ofindividual frames, e.g., row/column numbering, region/subregion/sector,etc., and all such schemes are considered within the scope of thepresent disclosure, however, such alternatives will not herein befurther discussed. Similarly, each NodeB in a wireless system can beidentified uniquely by a plurality of conventions, all of which arewithin the scope of the present disclosure, however only a “lettered”index is herein discussed, e.g., site j, site i, site k, etc. Where eachNodeB is uniquely identifiable, each pair of sites is also uniquelyidentifiable, e.g., pair ij, pair ik, pair jk, pair ji, pair ki, pairkj, etc. Further, NBSPs and frames can be identified parenthetically as“(NBSP, frame)”, wherein a question mark, ‘?’, can be used to indicatean arbitrary value, e.g., (ij,250) is the 250 frame in relation to NBSP“ij”, while (ij,?) is some undefined frame related to NBSP “ij”, (?,250)refers to frame 250 in relation to an undefined NBSP, and similarly(?,?) refers to an arbitrary NBSP and arbitrary frame.

For each pair of NodeBs, each frame of a subset of relevant framesassociated with the NBSP can have a value assigned that corresponds tothat frame's differential value. A subset can comprise some frames, allframes, or no frames (e.g., an empty set). A differential value can be ageometrically determined value related to the “distance” of a frame froma NBSP, measured in chip (e.g., “distance” can be a temporal or physicaldistance.) For known geometries, differential values can be pre-computedfor one, some, or all frames in a given frame set.

The NBSPs of TFL wireless environment 200 can each be associated with areference frame (?,R), for example, (ij,R), (jk,R), (ik,R), etc. Anobserved time difference, OV(?,?), can be related to the ‘C’ valuereported by a location aware UE of system 200. In an aspect, an OV(?,R)value can be directly obtained by data from location aware UEs at areference frame, R (e.g., UE 260 or UE 262 at reference frame 250 of TFLwireless environment 200.) In another aspect, where an OV(?,X) valuefrom a location aware UE is reported from an instant frame, X, otherthan the reference frame, R, the value can be translated to a referenceframe value based, at least in part, on known differential propagationdelays according to:

OV(ji,R)=OV(ji,X)+DV(ij,R)−DV(ij,X),   Eq. (1)

where

X identifies an instant frame, R identifies a reference frame, ijidentifies a NBSP, ji identifies a NBSP, DV(ij,R) is a differentialvalue for the reference frame of the NBSP ij that can be determined fromthe ij NBSP and reference frame geometry, DV(ij,X) is a differentialvalue for frame X for NBSP ij that can be determined from the ij NBSPand frame X geometry, and OV(ji,X) is an observed value for an frame Xof the ji NBSP, such that OV(ji,R) can be calculated. Moreover, OV(?,?)values can be weighted, for example, if a reporting UE is known to bemoving at a high rate of speed, the OV(?,?) can be of less relevance andtherefore can be given a lower weight. These weighted values can bestatistically manipulated to provide a more relevant value for OV(?,R),for example, by reducing measurement error effects.

Whereas DV(ij,R) is the geometrically determined differential value forthe reference frame of the ij NBSP, and having previously determined theobserved time difference value for the reference frame of the ji NBSP asOV(ji,R), Eq. 1 can be manipulated to determine the expected observedtime difference values for any instant frame, X, by simply determiningthe differential value for any instant frame, X, of the ji NBSP,DV(ji,X), and computing:

OV(ji,X)=OV(ji,R)+DV(ij,X)−DV(ij,R).   Eq. (2)

This equation can be similarly employed for other known NBSPs as well.In an aspect, this allows an indexed mapping of expected OV(?,?)value(s) for frame(s) of NBSP(s) given a known geometry for the NBSPsand bin grid, and an OV(?,R) reference cell value (e.g., ascertainedfrom location and time data from one or more location enabled UEsassociated with a NBSP, beacons, etc.)

FIG. 3 illustrates differential propagation delay sets for NBSPs in atime fingerprint location wireless environment 300 in accordance withaspects of the subject disclosure. TFL wireless environment 300 can bereferenced to a bin grid 310 and comprise one or more NodeBs (e.g., 320,322, 340). As disclosed herein, the differential values, DV(?,X), can begeometrically determined, and mapped to each frame for every known NBSP.In an aspect, this DV(?,?) mapping can be in the form of a table or setof tables to facilitate rapid access to the data. Further, in a NBSP,for example ij, where an OV(ji,X) value is ascertained and OV(ji,R) isknown, a corresponding DV(ij,X) value can be generated by:

DV(ij,X)=OV(ji,X)−OV(ji,R)+DV(ij,R),   Eq. (3)

which is obtained by simple manipulation of Eq. 2. This calculated valueof DV(ij,X) can function as a lookup value into the tabulated DV(?,X)data set(s), e.g., “return frames for NBSP ij having a DV(ij,X) valueequivalent to the computed value from Eq. 3.” The returned valuesgenerally will form a hyperbola for the NBSP when overlaid on ageographic map of the sites and bin grid framework. For the exemplary ijNBSP, the returned set can be referred to as the “ij primary set” andcan be represented by the set of shaded frames 326 between sites 320 and322, with corresponding ij NBSP reference frame 324.

In an aspect, UEs can be in an environment with a plurality of availableNBSPs, for example, a UE located in frame 360 can be exposed to NBSPs320/322, 320/340, and 322/340. NBSPs can return a related primary set.Prioritization of NBSPs can be beneficial by returning a primary set forthe most relevant NBSP. In accordance with an aspect of the disclosedsubject matter, a NBSP can be prioritized based, at least in part, onreceived signal code power (RSCP) which denotes the power measured by areceiver on a particular physical communication channel of the wirelessnetwork 300. For example, in FIG. 3, the NodeB RSCP values can behighest for 322, moderate for 340, and lowest for 320. Continuing thisnon-limiting example, the ordering of the NodeBs by RSCP can result inlooking up primary sets from pair 322/340 first, then 322/320 second,and 340/320 last. It will be appreciated by one of skill in the art thatother factors and criteria can be employed in determining what NBSPs areemployed for primary pair lookups, for example, confidence scores fordata sets, computational load aspects, number of requests in queue,cached primary sets, etc. It will further be appreciated that thesenumerous other factors and criteria are all within the scope of thepresent disclosure. As an additional non-limiting example, where NodeB320 has recently come online and has a relatively newer data set ascompared to 322 and 340, there may be a lower confidence in using thosevalues and priority can be given to other NBSPs for lookup.

In an aspect, determining a DV(?,X) can be related to calculating alocation for a UE time data (‘C’) (e.g., an OTD measured in anactive-state or idle-state) accessed for a non-location enabled UEwithout the mathematical complexity of hyperbola multilateration. Asdisclosed herein, where ‘A’ is relatively stable over hours or days, and‘C’ is accessed for a UE from a given NBSP, the ‘B’ value can becalculated and is related to the DV (in units of chip) from the givenNBSP. When UE time data is accessed, a DV(?,X) look-up can be initiated.Relevant NBSPs can be prioritized as part of the look-up, for example,by RSCP, etc. Further, the relevant pairs can be employed as an index tolookup a first primary set. As an example, in FIG. 3, time data for a UE(not illustrated) can be accessed in relation to a locating event in TFLwireless environment 300. In this example, it can be determined thatNBSP 322/340, with reference frame 342, be used for primary set lookupwith the computed DV(?,X) value as the index. This can for examplereturn the shaded frames 344 forming a hyperbola between NodeB 322 andNodeB 340 where DV(?,X) =DV(322/340,X). This indicates that the UE ismost likely located at one of the shaded frames of set 344. A secondlookup can then be performed for an additional relevant NBSP, forexample, NBSP 320/322, with reference frame 324, using the same valueDV(?,X), as an index into the data set. Continuing the example, thereturned set for the look up with DV(320/322,X)=DV(?,X) can return theset of shaded frames 326. Thus, the UE is also most likely located inthe shaded frames designated by set 326. Therefore, where the UE is mostlikely in both set 344 and set 326, it is clear that the most probablelocation for the UE is at the intersection of the two sets, at frame360.

It will be appreciated that additional lookups can be undertaken in anattempt to isolate the most likely frame by intersections of returnedsets and that this aspect is within the scope of the current disclosure.In a further aspect, where no exact match is found, frames within apredetermined distance of the closest match can be retained as eligible,for example, frames within 5 chips of the closest match. In anotheraspect, more or less granular data sets can be employed to give morerefined location results, for example, a more coarse granularity can beemployed so that a match can be obtained even where the locationfootprint area is larger. As a second example, a finer granularity canbe employed to better determine the location of a UE (e.g., a smallerfootprint area) where such a data set is available and an exact matchframe results. In some instances no single frame can be resolved (e.g.,insufficient data, too few NodeBs, etc.)

While the OTD measurement readily accessible for active-state UEs (e.g.,CFN-SFN OTD measurement), it can be less apparent that OTD measurementscan also be accessed from idle-state UEs. Given that ratios ofidle-state to active-state for UEs can often be high, for example, 22hours idle to 2 hours active for a cell phone, gathering OTD for anidle-state UE can provide valuable information for timing measurementswithin a wireless network. Thus, even where the population density foractive UEs in a region can be low (e.g., there may be many idle-stateUEs and relatively few active-state UEs), the timing lookup charts canbe kept fresh by employing idle-state OTD measurements in TFL-typecomputations. Wireless networks can include idle-state OTD measurementsin the standard, such that the idle-state OTDs can be employed indetermining location in accord with TFL techniques disclosed herein(e.g., the 3GPP standard at 25.331 v6.9 discloses that idle-state OTDcan be measured and reported, for example at section 10.3.7.45).

The idle-state OTDs can be reported to the TFL system (for example, toTFL Platform 410 in FIG. 4). For example, under the 3GPP standard, a SIB11 (or alternatively a SIB 12) message can be configured to request thatthe mobile report idle-state OTDs and the SIB11, or derivatives thereof,can be generated for networks associated with a TFL system. Typically,the OTDs associated with the SIB11 (or SIB 12) message are designatedfor measurement by setting appropriate parameter values for‘Intra-Frequency reporting quantity for RACH reporting’ and are reportedunder the ‘Measured Results on RACH’ (similarly, inter-frequencyreporting can be done by setting parameters on the ‘Inter-Frequencyreporting quantity for RACH reporting’), per 3GPP 25.331 v6.9 at.§10.3.7.42 and 10.3.7.43, etc. It will be appreciated by one of skill inthe art that these SFN-SFN OTDs can be provided in URA_PCH, CELL_PCH,CELL_FACH, and CELL_DCH modes (per 3GPP 24.215 v6.40). It will befurther appreciated by one of skill in the art that these or similarmeasurements, under future evolutions of the current 3GPP standard,standards other than 3GPP, and/or other future standards, are within thescope of the present disclosure where they relate to measuring timingdata in an idle-state for a UE and employing that idle-state measurementunder a TFL-type environment to facilitate location determinationsand/or timing determinations.

The ‘Measured Results on RACH’ (or other report of idle-state OTDs) canbe reported as a sub-component of another 3GPP specified message. Thesemessages can be of several types. For instance, a Cell-Update typemessage can include OTDs, for example, for a cell reselection, reactionto a radio link failure, in response to a page from the UTRAN, to notifythe UTRAN when re-entering a service area while in URA_PCH or CELL_PCHstates, for periodical updates, etc. Similarly, anInitial-Direct-Transfer type message can include OTDs, for example, forthe initial direct transfer procedure used to establish a signalingconnection in the uplink portion, to carry an initial upper layer (NAS)message over the radio interface, etc. Further, anRRC-Connection-Request type message can include OTDs, for example, forwhen triggered during voice calls, data calls, registrations, detaches,high and low priority signaling connections, inter-radio accesstechnology cell changes (IRAT), etc. Moreover, an Uplink-Direct-Transfertype message can include OTDs, for example, when used to carry an upperlayer (NAS) message over the radio interface, etc. One of skill in theart will appreciate that any of a wide variety of messages can include‘Measured Results on RACH’ or similar sub-messages to communicateidle-state OTDs, and that all such messages are within the scope of thepresent disclosure.

Whereas idle-state OTDs may not be mandated even where available forreport in response to a SIB11-type message, setting parameters wherethese OTDs are available can cause them to be reported out in accordancewith the design of a particular TFL system and wireless carrierenvironment. For example, in the 3GPP standard, the number of SFN-SFNOTDs measured and reported out can be adjusted by setting a parameterfor: no report, current cell, current cell+best neighbor, current cell+2best neighbors, . . . , current cell+6 best neighbors, etc. (see 3GPP25. 331 v6.9 at 10.3.7.43). In this 3GPP example, the idle-statedifferential OTD measurement for a TFL NBSP, as disclosed herein, canthus be ascertained by selecting, at least, “current cell+2 bestneighbors”. It can also be beneficial to select additional OTD reports(e.g., corresponding to additional OTD measurements for additional NBSPsfor a UE in an idle-state) up to the maximum number of reportable bestneighbors (e.g., as of v6.9 of section 25.331 of the 3GPP standard thisis +6 best neighbors). Further, measurements for both intra- andinter-frequency OTDs can be acquired and employed in computingdifferential measurements for NBSPs. Additionally, for the 3GPPstandard, the SFN-SFN observed time difference reporting indicator canbe specified as Type 1 or Type 2 capable, as will be appreciated by oneof skill in the art.

FIG. 4 illustrates a block diagram of an exemplary system 400 thatfacilitates time fingerprint location in accordance with aspectsdescribed herein. In an aspect, system 400 can be a part of a mobilenetwork, and can reside at least in part within at least one of anetwork management component (e.g., radio network controller, corenetwork, or network gateway) or a base station or access point. Examplesystem 400 includes a time fingerprint location (TFL) platform 410 thatfacilitates location of UEs based at least in part on receiving anobserved timing offset related to a frame. This observed time differencecan be ascertained from an active-state or idle-state UE as disclosedherein.

Calibration platform 410 includes a bin grid framing (BGF) component 412that can estimate the location of a mobile device or a stationary devicethat can communicate wirelessly. To at least that end, BGF component 412can include a bin grid (BG) model selector 414 that selects anappropriate bin grid based at least in part on the geometry of the NBSPsinteracting with the UE (not shown), e.g., selecting a particular subsetof a bin grid to include frames related to NBSPs relevant to locatingone or more UEs transmitting time data, select from bin grids ofdifferent granularity, selecting bin grid models related to updatingframe data, etc. The model can be utilized in conjunction with observedtime difference values (‘C’), propagation timing values (‘B’), and sitetiming values (‘A’) among forward link (FL) and reverse link (RL)wireless signals, e.g., signaling or traffic, delivered and received,respectively, by a base station or access point.

In an aspect, in exemplary system 400, TFL platform 410 can requestinformation (e.g., timing data, location data from a location enabledUE, etc.) from UEs through a FL wireless signal 436 that is conveyed bya signaling and traffic component 434 in a communication platform 430,which can be a part of a serving access point or NodeB. System 400 canaccess the requested information for UEs on a RL wireless signal 438, inthe RL counterpart transport channel (e.g., in relation to a SIB11 orSIB12, etc.). It should be appreciated that communication platform 430includes antenna(s) 432.

As described above, BGF component 412 can estimate location of a mobiledevice by at least in part searching computed location data sets forNBSPs and timing data that correlates to the computed values. The clocklayer 416 can facilitate determining the propagation delay (‘B’), forexample from accessing an observed time difference (‘C’). It is notedthat such returned timing data is typically part of basic, conventionalUE RAN operation, and no additional equipment is necessary to generatesuch data in most cases. Where such equipment is needed, it can beincluded and should be considered within the scope of the presentlydisclosed subject matter. Further, where such data can be acquired byselecting an appropriate parameter set within a given wireless networkdeployment, such parameters can be appropriately set to return thedesired data. Returned timing data in conjunction with bin gridframeworks can provide a location estimate as disclosed herein.Calibration platform 410 also includes analysis component 418 that canimplement various algorithms, stored in algorithm storage 444, tocharacterize or evaluate various features of the returned location data,location estimates, etc., generated by BGF component 412. In an aspect,algorithms employed by analysis component 418 include statisticalanalysis methodologies; other analysis methodologies such as spectralanalysis and time-series analysis also can be utilized. Location datacan be cached in frame location storage 432. Frame location storage canbe communicatively coupled to other data storage locations (notillustrated), either locally or remotely, to facilitate sharing andupdating of the frame location information.

In an aspect, system 400 can facilitate compensation of wireless signal(e.g., RF, microwave, infrared . . . ) timing variations, or correctionof wireless signal propagation information by way of TFL platform 410.TFL platform 410 can access location and time data from location awareUEs (e.g., as part of UEs 420) and time data from non-location aware UEs(e.g., as part of UEs 420), either in an active-state or idle-state.This timing and/or location data can be made available to datamanagement component 411. Accessed location and/or timing data 415 canbe retained in frame location storage 442 as raw data, processed data,data converted into frame data, etc. It should be appreciated that basedupon specific aspects of the UEs 220, TFL platform 410 can accesslocation and/or timing data 415 over an air-interface by way ofcommunication platform 430, or through a network management componentsuch as a network server, a radio network controller, or a networkgateway. UEs 420 can provide location and/or timing data based, at leastin part, on GNSS, such as assisted GPS, and network planninginformation. In an aspect, the UEs 420 comprise a set of mobile devicesthat, at least in part, support GNSS data reception and manipulationthereof. For example, these UEs can communicate with a GNSS system(e.g., GPS, Galileo, GLONASS . . . ) through a deep-space link. TheseUEs can receive timing signaling that allows determination, at least inpart, of accurate position of each UE that receives sufficientinformation (e.g., timing information from three or more satellites) fortriangulation. Alternatively, UEs can receive assisted timinginformation from mobile network platform(s), through base stationsserving a relevant sector, mobile network platform(s) received timinginformation from GNSS through deep-space links, etc. Such timinginformation or location information can be received at various timeinstants and aggregated at TFL platform 410 through analysis component418. Aggregation collects location and timing data received at variousinstants in time in order to augment the statistical significance ofdata and analysis thereof, which can improve accuracy of extractedlocation determinations and related propagation delay data.

FIG. 5 depicts additional or alternative timing and/or location data 415generation components 520 ₁-520 ₃ that are not UEs 420 (e.g.,calibration beacons, femto or pico cell equipment, etc.) to facilitatecalibration of reference frames in a bin grid framework (e.g., 210, 310,etc.). Known locations for a set of probes, or wireless beacons,deployed within a coverage cell or sector, as illustrated, can beemployed to determine ‘A’ and ‘B’ in a manner similar to a locationaware UE. For example, macro coverage cell 500 is divided in threesectors (demarcated by dashed lines) served by base station 510, whereina sector includes a set of three probes 520 ₁-520 ₃ located at specificpositions that are known, or available, to the one or more networkcomponents (e.g., mobile network platform(s) 108). Probes 520 ₁-520 ₃also communicate with base station 510 through wireless links 515.Communicated time data and a known position of the probes 520 ₁-520 ₃allows calculation of the ‘A’ and ‘B’ values as disclosed herein.Wireless probes, or beacons, can be stationary or pseudo-stationary. Inan example, wireless probes can be Wi-Fi outdoor access points that arepart of a public metropolitan network. In another example, wirelessprobes can be part of wireless-enabled utility equipment (e.g., electricmeter(s)) deployed within a utility network, e.g., electric grid. Itshould be appreciated that wireless beacons embodied in utility meterscan be better suited for smaller, urban coverage sectors, sincetransmission power of such probes can be low compared to power formWi-Fi access points.

Various aspects of the disclosed subject matter can be automated throughartificial intelligence (AI) methods to infer (e.g., reason and draw aconclusion based upon a set of metrics, arguments, or known outcomes incontrolled scenarios) suitable models for propagation of wirelesssignal, e.g., RF signal, microwave signal, etc.; optimal or near-optimalpositions for probes that enable generation of accurate locationestimates; or the like. Artificial intelligence techniques typicallyapply advanced mathematical algorithms—e.g., decision trees, neuralnetworks, regression analysis, principal component analysis (PCA) forfeature and pattern extraction, cluster analysis, genetic algorithm, orreinforced learning—to a data set; e.g., the collected subscriberintelligence in the case of subscriber segmentation. In particular, oneof numerous methodologies can be employed for learning from data andthen drawing inferences from the models so constructed. For example,Hidden Markov Models (HMMs) and related prototypical dependency modelscan be employed. General probabilistic graphical models, such asDempster-Shafer networks and Bayesian networks like those created bystructure search using a Bayesian model score or approximation also canbe utilized. In addition, linear classifiers, such as support vectormachines (SVMs), non-linear classifiers like methods referred to as“neural network” methodologies, fuzzy logic methodologies also can beemployed.

In view of the example system(s) described above, example method(s) thatcan be implemented in accordance with the disclosed subject matter canbe better appreciated with reference to flowcharts in FIG. 6-FIG. 9. Forpurposes of simplicity of explanation, example methods disclosed hereinare presented and described as a series of acts; however, it is to beunderstood and appreciated that the claimed subject matter is notlimited by the order of acts, as some acts may occur in different ordersand/or concurrently with other acts from that shown and describedherein. For example, one or more example methods disclosed herein couldalternatively be represented as a series of interrelated states orevents, such as in a state diagram. Moreover, interaction diagram(s) mayrepresent methods in accordance with the disclosed subject matter whendisparate entities enact disparate portions of the methodologies.Furthermore, not all illustrated acts may be required to implement adescribed example method in accordance with the subject specification.Further yet, two or more of the disclosed example methods can beimplemented in combination with each other, to accomplish one or morefeatures or advantages herein described. It should be furtherappreciated that the example methods disclosed throughout the subjectspecification are capable of being stored on an article of manufactureto allow transporting and transferring such methods to computers forexecution, and thus implementation, by a processor or for storage in amemory.

FIG. 6 presents a flowchart of an exemplary method 600 for determining alocation for a UE. The location determination can facilitate correctingRF propagation delay information in an operational wireless systemaccording to aspects described herein. Further, location information canbe leveraged to provide location-centric information and services tousers associated with UEs, for example, maps, events, sales, or socialnetworking services, etc. Location-centric information and services canalso be employed to provide additional services and products by way ofaggregation of location information, for example, traffic data, usagedata, or demographic data, among others. Still further, certain locationdependant services can leverage location determinations of UEs, forexample, E911. The subject exemplary method 600, while illustrated forRF signal, also can be employed with regard to electromagnetic radiation(EM) with frequencies other than radio frequency, for instance,microwave EM radiation, infrared radiation, etc. In an aspect, thesubject exemplary method 600 can be implemented by one or more networkcomponents, e.g., TFL platform 410. Alternatively or additionally, aprocessor (e.g., processor 450) configured to confer, and that confers,at least in part, functionality to the one or more network componentscan enact the subject exemplary method 600. At 610, an OV(?,R) value isdetermined. For example, OV(?,R) can be a idle-stated OTD reported for aUE in the TFL network as disclosed herein. The determined OV(?,R) valuecan be based, at least in part, on a time difference between a NBSP inthe TFL wireless network and a UE. In an aspect, the OV(?,R) can bedetermined by solving Eq. 1 where DV(?,R) and DV(?,X) can be determinedbased on the geographical location of the reference frame R and theinstant frame X from the relevant NBSP, and where the received timedifference is OV(?,X). For example, OV(?,X) can be a idle-stated OTD,similar to OV(?,R), and can be reported for a UE in the TFL network asdisclosed herein. Further, as described herein, in an aspect, where alocation aware UE is available to provide data for the reference frameR, OV(?,R) can be calculated directly as equivalent to the OV(?,X)because X=R under these conditions. Further, location aware UEs that cansupport reception of GNSS data, such as assisted GPS (AGPS), andoperation thereon (e.g., injection of GNSS data on location basedapplications that execute, or are native, to the mobile) or manipulationthereof, such as delivery of location data, can easily provide access tothis location information. This location information can facilitaterapid geographical location of an instant frame X of the TFL wirelessnetwork, such that the DV(?,?) values can be rapidly calculated andemployed in translating OV(?,X) values into OV(?,R) values.Additionally, location determinations can be accumulated, weighted,and/or otherwise statistically manipulated to provide improvements tothe resulting value, for example, averaging over a plurality of OV(?,R)can be employed to reduce certain types of error propagation. In afurther aspect, the location information can be accessed through networkcomponents that retain known locations, for example, location probes orwireless beacons (e.g., probes 520 ₁-520 ₃). As an example, wirelessbeacons can be fixed location Wi-Fi outdoor access points that are partof a public metropolitan network.

At 620, the differential value DV(?,R) can be determined for thereference frame R. This can be done as part of the determination ofOV(?,R) at 610, or in circumstances where a DV(?,R) is not determined aspart of 610, it can be determined separately at 620, for example, wherea location aware UE facilitated determining OV(?,R) directly at 610,DV(?,R) can be determined separately at 620.

At 630, a differential value DV(?,?) can be determined for frames of abin grid framework and for NBSPs of relevance. Given that NBSP (e.g., afirst and second NodeB) locations are typically well defined physicallocations, the differential value, DV(?,?), can be geometricallydetermined (measured in chips) because the geographic location of eachframe is defined by the bin grid framework in relation to each relevantNBSP. In an aspect, a NBSP can be associated with a limited set ofspecific frames for which the NBSP is relevant. For example, a NBSPlocated in San Diego, Calif. would not be relevant to bin grid frames inRedding, Calif. Thus, the relevant frames can be limited to those ofsignificant value to any specific NBSP. As a non-limiting example, eachNBSP can be limited to an arbitrary number of the closest frames, forexample, 4096 frames. This can serve to reduce data that would otherwisebe of little value.

At 640, a database of bin grid frame locations can be updated withDV(?,?) values for each relevant NBSP. These values can be an indexthrough the tabulated data. These indexes can be employed to findrelevant frame locations, for example, by using an SQL-type query on theindexed data. Where large volumes of data are developed for one or morebin grid frameworks, these datasets can be indexed for fast searchingand can be stored in subsets for particular areas or NBSPs. For example,a bin grid frame location data set can include NBSP indices for a city,county, state, region, country, etc. As another non-limiting example, adata set for a first NodeB and other NodeBs that pair with the firstNodeB can be stored at the first NodeB to facilitate indexed look-ups offrame locations for any NBSP involving the first NodeB. Further, forexample, larger data sets having a plurality of NBSPs (e.g., city wide,regional, etc.) can, for example, include separate NBSP indices as a wayof rapidly traversing data for a frame location look-up.

In an aspect, statistical analysis of the data, e.g., frame locationsand DV(?,?) index values are utilized to establish a correlation betweenpropagation values for multiple NBSPs (e.g., a differential locations)to facilitate structured data analysis that returns a match or limitedset of potential matches for a UE location. These location values can beconverted into propagation times because the measurements can be inchips. This can allow for correction and compensation of wirelessnetwork timing values as well as allowing for location-centric servicesand information aggregation. It should be appreciated that statisticalmetrics can also be employed to quantify a correlation among locationdata information, particularly in aggregated location data applications.

At act 650, a differential value, DV(?,X), for a frame X can bedetermined. For example, Eq. 3 can be employed to determine DV(?,X) fora given OV(?,X) where DV(?,R) and OV(?,R) have already been determined.Further, DV(?,X) can be reported directly from an active-state oridle-state UE, or computed from a reported OV(?,X) from an active-stateor idle-state UE. For example, an idle-state UE can report DV(?,X) inresponse to a SIB 11 (or SIB 12) message for one or more NBSPs, asdisclosed herein. At 660, a frame location set can be found and returnedfrom the database based, at least in part, on DV(?,X) and the relevantNBSP as indexes. At this point method 600 can end. As a non-limitingexample, for any given NBSP and index DV(?,X) value, 150 frames withmatching DV(?,?) values can be returned. This indicates that the UE withthe DV(?,X) value is likely located in one of the 150 frames returned.These frames typically correspond to a hyperbola between the NodeBs ofthe indicated NBSP. One advantage is that the index values for theframes are pre-computed and complex math is not required at lookup toget the resulting set as would be required in a traditionalmultilateration technique. The value of the pre-computation and lookupaspect of the disclosed subject matter becomes significantly moreprominent when numerous NBSPs are searched for the same DV(?,X) value.The increase in complexity for traditional multilateration techniques isfactorial and quickly becomes computationally intensive. In contrast,the lookup technique remains comparatively computationally simple, evenover large sets of data. As an example, a relevant set of NBSP framelocations for a given DV(?,X) value is likely to intercept another framelocation set for a different relevant NBSP in a limited number of framelocations. This can rapidly result in convergence on a singular framelocation of the two or more sets without the need for any complex mathat the time of lookup.

It is noted that the subject example method 600 can be employed forlocation of UE, including UE in an idle-state, in a TFL wireless network(e.g., 200, 300) and compensation of RF signal propagation delay invarious operational wireless system such as macro coverage wirelesssystems; radar systems; home-based wireless systems, e.g., micro cell,pico cell, femto cell, Wi-Fi hot spot; or the like. It should beappreciated that for the various aforementioned wireless technologies,propagation of RF signal(s), microwave signal(s), infrared signal(s), orany other radiation signal(s), is implemented by a radio communicationcomponent, e.g., signaling and traffic component 434, that can residewithin an access point that operates in accordance with a respectivewireless technology.

FIG. 7 is a flowchart of an exemplary method 700 for iterativelydetermining a location of a UE in a TFL wireless network according toaspects of the disclosed subject matter. The subject example method 700can be implemented by one or more network components, e.g., TFL platform410. Alternatively or additionally, a processor (e.g., processor 450)configured to confer, and that confers, at least in part, functionalityto the one or more network components can enact the subject examplemethod 700.

At 710, a database of frame locations is updated with differentiallocation values and NBSP identification values. Updating the DV(?,?)indices and the NBSP indices for frame location keeps the dataset wellmaintained over time as values can drift and NBSPs can change as sitesare commissioned, decommissioned, taken down for service, or return fromservice, for example. Where a NodeB, for example, unexpectedly goesoffline, all existing DV(?,?) values for NBSPs including the offlineNodeB will be immediately invalid. Hence, updates to the databaserecords to, for example, remove NBSPs attached to the offline NodeB willhelp to keep location lookups in that region relevant and accurate.

At 720, a differential location value for a UE can be determined. Thiscan be calculated from the time data transmitted by the UE by way of Eq.3 where the remaining values are known. This can also be directlyreported out by employing a SIB11 or SIB12 message as disclosed herein,for example, by an idle-state UE reporting OTDs for at least one NBSP(i.e. “cell+2 best neighbors” parameter selected). Further, a first NBSPcan be determined/selected as a database index term. For example, RSCPvalues can indicate the closest NBSPs from which the most relevant setcan be selected as a first index. Other examples of selecting relevantNBSPs can include selecting sites that have statistically reliable dataassociated with them, selecting pairs that are related to a generaldirection of travel, availability of look-up resources at variousnetwork components, etc.

At 730, a set of frame locations is returned from the database search ofthe selected NBSP and DV(?,X) value searched. As disclosed herein, thisset can include zero, one, some, or all frame locations. As anon-limiting example, a search can return, say, 150 frame locations inthe frame location set.

At 740, for each iteration, only frames in both the current and previousset are retained. For a first iteration, all frames in the set can bekept.

At 750, a determination is made based on the number of frame locationsin the frame location set. Where there is more than one frame in theframe location set, the method passes to 760. Where there is only oneframe in the set, the method 700 can proceed to 770.

At 760, the NBSP can be incremented and the method 700 can return to730. Upon the return to 730, the DV(?,X) value can be searched again butthis time indexed with the next relevant NBSP. The method at 730 canreturn a new frame location set and proceed to 740. At 740 for thesecond iteration, the frames of the new set and the preceding set can becompared and frames found in both sets can be retained in the frame set,such that upon subsequent iterations, this retained set can be comparedto subsequent new frame location sets and a single value can beconverged on iteratively. At 750, a determination can be made againrelating to the number of frame locations in the frame location set.This process can continue until a predetermined number of framelocations, for example, a single frame location, are present in theframe location set. One of skill in the art will appreciate thatnon-convergent behavior is not discusses herein, but that such behavioris within the scope of the disclosure. For example, where the behavioris non-convergent, the method can end without satisfying the decision at750.

At 770, the remaining frame location(s) can be equated to the locationof the UE and the UE location can be updated to reflect thisdetermination. At this point method 700 can end.

FIG. 8 presents a flowchart of an example method 800 for updating sitetiming values according to aspects of the disclosed subject matterdescribed herein. The subject example method 800 can be implemented byone or more network components, e.g., TFL platform 410. Alternatively oradditionally, a processor (e.g., processor 450) configured to confer,and that confers, at least in part, functionality to the one or morenetwork components can enact the subject example method 800.

At 810, an OV(?,R) update value can be determined. This can be based, atleast in part, on a location aware UE providing an updated observedtiming difference, including idle-state OTDs, e.g., OV(?,X), andlocation data. From this, OV(?,X) can be translated to OV(?,R), asdisclosed previously herein, by Eq. 1.

At 820, the determined OV(?,R) update value can be weighted and combinedwith the then current value of OV(?,R). This can provide additionalrobustness to the reference frame observed value, which relates to sitetiming in the wireless network as disclosed herein. One example of thistype of updating is weighted averaging, which can reduce randommeasurement errors. One of skill in the art will appreciate thatnumerous other types of statistical transformations can be applied toimprove the quality of the measured value in light of subsequentmeasurements, all such manipulations are believed to be within the scopeof the presently disclosed subject matter.

At 830, the updated OV(?,R) value can be employed while not crossing athreshold value. Additional updates to the OV(?,R) can be accomplishedby looping back to 810 from 830, as illustrated, even where no thresholdvalue has been exceeded. An example of this type of OV(?,R) update valuefrom 830 can include a location aware UE coming into a network andproviding additional OV(?,X) data and location data such that an OV(?,R)update can be calculated and incorporated. At this point, this branchcan cause method 800 to end.

At 840, where a threshold value has been crossed, the existing OV(?,R)value can be purged and a new value can be applied. In an aspect thisnew OV(?,R) value can be based on data from location aware UE reports.In another aspect, this value can be a previously stored value from aknown operational state. The purging and replacement of this value canoccur, for example, where NBSP conditions have drastically changed andthe existing site timing information can include errors. An example ofconditions that might precipitate this behavior can include equipmentfailure, poorly performing equipment, natural disaster, construction,etc. From 840, method 800 can return to 810 and iteratively update thenew value of OV(?,R) as herein described. At this point method 800 canend.

FIG. 9 illustrates a block diagram of an example embodiment of an accesspoint to implement and exploit one or more features or aspects of thedisclosed subject matter. In embodiment 900, AP 905 can receive andtransmit signal(s) (e.g., attachment signaling) from and to wirelessdevices like femto access points, access terminals, wireless ports androuters, or the like, through a set of antennas 920 ₁-920 _(N) (N is apositive integer). It should be appreciated that antennas 920 ₁-920 _(N)embody antenna(s) 432, and are a part of communication platform 915,which comprises electronic components and associated circuitry thatprovides for processing and manipulation of received signal(s) andsignal(s) to be transmitted. Such electronic components and circuitryembody at least in part signaling and traffic component 434;communication platform 915 operates in substantially the same manner ascommunication platform 430 described hereinbefore. In an aspect,communication platform 915 includes a receiver/transmitter 916 that canconvert signal (e.g., RL signal 438) from analog to digital uponreception, and from digital to analog upon transmission. In addition,receiver/transmitter 916 can divide a single data stream into multiple,parallel data streams, or perform the reciprocal operation. Coupled toreceiver/transmitter 916 is a multiplexer/demultiplexer 917 thatfacilitates manipulation of signal in time and frequency space.Electronic component 917 can multiplex information (data/traffic andcontrol/signaling) according to various multiplexing schemes such astime division multiplexing (TDM), frequency division multiplexing (FDM),orthogonal frequency division multiplexing (OFDM), code divisionmultiplexing (CDM), space division multiplexing (SDM). In addition,mux/demux component 917 can scramble and spread information (e.g.,codes) according to substantially any code known in the art; e.g.,Hadamard-Walsh codes, Baker codes, Kasami codes, polyphase codes, and soon. A modulator/demodulator 918 is also a part of communication platform915, and can modulate information according to multiple modulationtechniques, such as frequency modulation, amplitude modulation (e.g.,M-ary quadrature amplitude modulation (QAM), with M a positive integer),phase-shift keying (PSK), and the like. Communication platform 915 alsoincludes a coder/decoder (codec) component 919 that facilitates decodingreceived signal(s), and coding signal(s) to convey.

Access point 905 also includes a processor 935 configured to conferfunctionality, at least in part, to substantially any electroniccomponent in AP 905. In particular, processor 935 can facilitatedetermination of propagation delay information of RF signal, ormicrowave signal, among communication platform 915 and antennas 920₁-920 _(N) in accordance with various aspects and embodiments disclosedherein. Power supply 925 can attach to a power grid and include one ormore transformers to achieve power level that can operate AP 905components and circuitry. Additionally, power supply 925 can include arechargeable power component to ensure operation when AP 905 isdisconnected from the power grid, or in instances, the power grid is notoperating.

Processor 935 also is functionally connected to communication platform915 and can facilitate operations on data (e.g., symbols, bits, orchips) for multiplexing/demultiplexing, such as effecting direct andinverse fast Fourier transforms, selection of modulation rates,selection of data packet formats, inter-packet times, etc. Moreover,processor 935 is functionally connected, via a data or system bus, tocalibration platform 912 and other components (not shown) to confer, atleast in part functionality to each of such components.

In AP 905, memory 945 can store data structures, code instructions andprogram modules, system or device information, code sequences forscrambling, spreading and pilot transmission, location intelligencestorage, determined delay offset(s), over-the-air propagation models,and so on. Processor 935 is coupled to the memory 945 in order to storeand retrieve information necessary to operate and/or conferfunctionality to communication platform 915, calibration platform 912,and other components (not shown) of access point 905.

FIG. 10 presents an example embodiment 1000 of a mobile network platform1010 that can implement and exploit one or more aspects of the disclosedsubject matter described herein. Generally, wireless network platform1010 can include components, e.g., nodes, gateways, interfaces, servers,or disparate platforms, that facilitate both packet-switched (PS) (e.g.,internet protocol (IP), frame relay, asynchronous transfer mode (ATM))and circuit-switched (CS) traffic (e.g., voice and data), as well ascontrol generation for networked wireless telecommunication. Mobilenetwork platform 1010 includes CS gateway node(s) 1012 which caninterface CS traffic received from legacy networks like telephonynetwork(s) 1040 (e.g., public switched telephone network (PSTN), orpublic land mobile network (PLMN)) or a signaling system #7 (SS7)network 1070. Circuit switched gateway node(s) 1012 can authorize andauthenticate traffic (e.g., voice) arising from such networks.Additionally, CS gateway node(s) 1012 can access mobility, or roaming,data generated through SS7 network 1070; for instance, mobility datastored in a visited location register (VLR), which can reside in memory1030. Moreover, CS gateway node(s) 1012 interfaces CS-based traffic andsignaling and PS gateway node(s) 1018. As an example, in a 3GPP UMTSnetwork, CS gateway node(s) 1012 can be realized at least in part ingateway GPRS support node(s) (GGSN). It should be appreciated thatfunctionality and specific operation of CS gateway node(s) 1012, PSgateway node(s) 1018, and serving node(s) 1016, is provided and dictatedby radio technology(ies) utilized by mobile network platform 1010 fortelecommunication.

In the disclosed subject matter, in addition to receiving and processingCS-switched traffic and signaling, PS gateway node(s) 1018 can authorizeand authenticate PS-based data sessions with served mobile devices. Datasessions can include traffic, or content(s), exchanged with networksexternal to the wireless network platform 1010, like wide areanetwork(s) (WANs) 1050, enterprise network(s) 1070, and servicenetwork(s) 1080, which can be embodied in local area network(s) (LANs),can also be interfaced with mobile network platform 1010 through PSgateway node(s) 1018. It is to be noted that WANs 1050 and enterprisenetwork(s) 1060 can embody, at least in part, a service network(s) likeIP multimedia subsystem (IMS). Based on radio technology layer(s)available in technology resource(s) 1017, packet-switched gatewaynode(s) 1018 can generate packet data protocol contexts when a datasession is established; other data structures that facilitate routing ofpacketized data also can be generated. To that end, in an aspect, PSgateway node(s) 1018 can include a tunnel interface (e.g., tunneltermination gateway (TTG) in 3GPP UMTS network(s) (not shown)) which canfacilitate packetized communication with disparate wireless network(s),such as Wi-Fi networks.

In embodiment 1000, wireless network platform 1010 also includes servingnode(s) 1016 that, based upon available radio technology layer(s) withintechnology resource(s) 1017, convey the various packetized flows of datastreams received through PS gateway node(s) 1018. It is to be noted thatfor technology resource(s) 1017 that rely primarily on CS communication,server node(s) can deliver traffic without reliance on PS gatewaynode(s) 1018; for example, server node(s) can embody at least in part amobile switching center. As an example, in a 3GPP UMTS network, servingnode(s) 1016 can be embodied in serving GPRS support node(s) (SGSN).

For radio technologies that exploit packetized communication, server(s)1014 in wireless network platform 1010 can execute numerous applications(e.g., location services, online gaming, wireless banking, wirelessdevice management . . . ) that can generate multiple disparatepacketized data streams or flows, and manage (e.g., schedule, queue,format . . . ) such flows. Such application(s) can include add-onfeatures to standard services (for example, provisioning, billing,customer support . . . ) provided by wireless network platform 1010.Data streams (e.g., content(s) that are part of a voice call or datasession) can be conveyed to PS gateway node(s) 1018 forauthorization/authentication and initiation of a data session, and toserving node(s) 1016 for communication thereafter. In addition toapplication server, server(s) 1014 can include utility server(s), autility server can include a provisioning server, an operations andmaintenance server, a security server that can implement at least inpart a certificate authority and firewalls as well as other securitymechanisms, and the like. In an aspect, security server(s) securecommunication served through wireless network platform 1010 to ensurenetwork's operation and data integrity in addition to authorization andauthentication procedures that CS gateway node(s) 1012 and PS gatewaynode(s) 1018 can enact. Moreover, provisioning server(s) can provisionservices from external network(s) like networks operated by a disparateservice provider; for instance, WAN 1050 or Global Positioning System(GPS) network(s) (not shown). Provisioning server(s) can also provisioncoverage through networks associated to wireless network platform 1010(e.g., deployed and operated by the same service provider), such asfemto cell network(s) (not shown) that enhance wireless service coveragewithin indoor confined spaces and offload RAN resources in order toenhance subscriber service experience within a home or businessenvironment. Server(s) 1014 can embody, at least in part, TFL platform410 and any component(s) therein

It is to be noted that server(s) 1014 can include one or more processorsconfigured to confer at least in part the functionality of macro networkplatform 1010. To that end, the one or more processor can execute codeinstructions stored in memory 1030, for example. It is should beappreciated that server(s) 1014 can include a content manager 1015,which operates in substantially the same manner as describedhereinbefore.

In example embodiment 1000, memory 1030 can store information related tooperation of wireless network platform 1010. In particular, memory 1030can include contents of memory 440 in example system 400. Otheroperational information can include provisioning information of mobiledevices served through wireless platform network 1010, subscriberdatabases; application intelligence, pricing schemes, e.g., promotionalrates, flat-rate programs, couponing campaigns; technicalspecification(s) consistent with telecommunication protocols foroperation of disparate radio, or wireless, technology layers; and soforth. Memory 1030 can also store information from at least one oftelephony network(s) 1040, WAN 1050, enterprise network(s) 1060, or SS7network 1070.

It is to be noted that aspects, features, or advantages of the disclosedsubject matter described in the subject specification can be exploitedin substantially any wireless communication technology. For instance,Wi-Fi, WiMAX, Enhanced GPRS, 3GPP LTE, 3GPP2 UMB, 3GPP UMTS, HSPA,HSDPA, HSUPA,GERAN, UTRAN, LTE Advanced. Additionally, substantially allaspects of the disclosed subject matter as disclosed in the subjectspecification can be exploited in legacy telecommunication technologies;e.g., GSM. In addition, mobile as well non-mobile networks (e.g.,internet, data service network such as internet protocol television(IPTV)) can exploit aspects or features described herein.

Various aspects or features described herein can be implemented as amethod, apparatus or system, or article of manufacture using standardprogramming or engineering techniques. In addition, various aspects orfeatures disclosed in the subject specification also can be effectedthrough program modules that implement at least one or more of themethods disclosed herein, the program modules being stored in a memoryand executed by at least a processor. Other combinations of hardware andsoftware or hardware and firmware can enable or implement aspectsdescribed herein, including disclosed method(s). The term “article ofmanufacture” as used herein is intended to encompass a computer programaccessible from any computer-readable device, carrier, or media. Forexample, computer readable media can include but are not limited tomagnetic storage devices (e.g., hard disk, floppy disk, magnetic strips. . . ), optical discs (e.g., compact disc (CD), digital versatile disc(DVD), blu-ray disc (BD) . . . ), smart cards, and flash memory devices(e.g., card, stick, key drive . . . ).

As it employed in the subject specification, the term “processor” canrefer to substantially any computing processing unit or devicecomprising, but not limited to comprising, single-core processors;single-processors with software multithread execution capability;multi-core processors; multi-core processors with software multithreadexecution capability; multi-core processors with hardware multithreadtechnology; parallel platforms; and parallel platforms with distributedshared memory. Additionally, a processor can refer to an integratedcircuit, an application specific integrated circuit (ASIC), a digitalsignal processor (DSP), a field programmable gate array (FPGA), aprogrammable logic controller (PLC), a complex programmable logic device(CPLD), a discrete gate or transistor logic, discrete hardwarecomponents, or any combination thereof designed to perform the functionsdescribed herein. Processors can exploit nano-scale architectures suchas, but not limited to, molecular and quantum-dot based transistors,switches and gates, in order to optimize space usage or enhanceperformance of user equipment. A processor may also be implemented as acombination of computing processing units.

In the subject specification, terms such as “store,” “storage,” “datastore,” data storage,” “database,” and substantially any otherinformation storage component relevant to operation and functionality ofa component, refer to “memory components,” or entities embodied in a“memory” or components comprising the memory. It will be appreciatedthat the memory components described herein can be either volatilememory or nonvolatile memory, or can include both volatile andnonvolatile memory.

By way of illustration, and not limitation, nonvolatile memory caninclude read only memory (ROM), programmable ROM (PROM), electricallyprogrammable ROM (EPROM), electrically erasable ROM (EEPROM), or flashmemory. Volatile memory can include random access memory (RAM), whichacts as external cache memory. By way of illustration and notlimitation, RAM is available in many forms such as synchronous RAM(SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rateSDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), anddirect Rambus RAM (DRRAM). Additionally, the disclosed memory componentsof systems or methods herein are intended to comprise, without beinglimited to comprising, these and any other suitable types of memory.

What has been described above includes examples of systems and methodsthat provide advantages of the disclosed subject matter. It is, ofcourse, not possible to describe every conceivable combination ofcomponents or methodologies for purposes of describing the disclosedsubject matter, but one of ordinary skill in the art may recognize thatmany further combinations and permutations of the claimed subject matterare possible. Furthermore, to the extent that the terms “includes,”“has,” “possesses,” and the like are used in the detailed description,claims, appendices and drawings such terms are intended to be inclusivein a manner similar to the term “comprising” as “comprising” isinterpreted when employed as a transitional word in a claim.

1. A non-transitory computer-readable storage medium storingcomputer-executable instructions that, in response to execution, cause asystem including a processor to perform operations, comprising:receiving a first observed time value associated with wireless cellularradio links between a first pair of radios of a wireless network and auser equipment of the wireless network, wherein the user equipment ispowered on and not in an active call session; and determining a firstdifferential time value based, at least in part, on the first observedtime value, a first reference observed time value, and a first referencedifferential time value.
 2. The non-transitory computer-readable storagemedium of claim 1, wherein the operations further comprise: determininga location for the user equipment based, at least in part, on the firstdifferential time value.
 3. A method, comprising: receiving, by a systemincluding a processor, a first observed time value associated with firstradio links between a first pair of radios of a wireless network and auser equipment in the wireless network, wherein the user equipment is inan idle-state; and determining, by the system, a first differential timevalue based on the first observed time value, a first reference observedtime value, and a first reference differential time value.
 4. The methodof claim 3, wherein the determining the first differential time valueincludes subtracting the first reference observed time value from thefirst observed time value and adding the first reference differentialtime value.
 5. The method of claim 3, wherein the receiving the firstobserved time value includes receiving the first observed time valuebased, at least in part, on a first propagation time for a first radiosignal between a first radio of the first pair of radios and the userequipment, a second propagation time for a second radio signal between asecond radio of the first pair of radios and the user equipment, a firstdelay time associated with the first radio, and a second delay timeassociated with the second radio.
 6. The method of claim 3, wherein thefirst reference observed time value and the first reference differentialtime value are predetermined, and a first radio of the first pair ofradios is at least part of a base station of the wireless network. 7.The method of claim 3, further comprising: determining, by the system, alocation for the user equipment based on the first differential timevalue.
 8. The method of claim 7, wherein the determining the locationincludes comparing the first differential time value to a set ofpredetermined differential values associated with the first pair ofradios.
 9. The method of claim 7, wherein the determining the locationincludes receiving a set of potential locations includes comparing thefirst differential time value to a set of predetermined differentialvalues associated with the first pair of radios.
 10. The method of claim3, further comprising: receiving, by the system, a second observed timevalue associated with second radio links between a second pair of radiosof the wireless network and the user equipment, wherein the second pairof radios is different from the first pair of radios; and determining,by the system, a second differential time value based, at least in part,on the second observed time value, a second reference observed timevalue, and a second reference differential time value.
 11. The method ofclaim 10, wherein the receiving the first observed time value includesreceiving the first observed time value associated with the first radiolinks between the first pair of radios and the user equipment, whereinthe first pair of radios comprises a first radio and a second radio,wherein the receiving the second observed time value includes receivingthe second observed time value associated with the second radio linksbetween the second pair of radios and the user equipment, and whereinthe second pair of radios comprises the second radio and a third radio.12. The method of claim 10, wherein the receiving the first observedtime value includes receiving the first observed time value associatedwith the first radio links between the first pair of radios and the userequipment, wherein the first pair of radios comprises a first radio anda second radio, wherein the receiving the second observed time valueincludes receiving the second observed time value associated with thesecond radio links between the second pair of radios and the userequipment, and wherein the second pair of radios comprises a third radioand a fourth radio.
 13. The method of claim 10, further comprising:determining, by the system, a location for the user equipment based, atleast in part, on the first differential time value and the seconddifferential time value.
 14. The method of claim 13, wherein thedetermining the location includes comparing the first differential timevalue to a first set of predetermined differential values associatedwith the first pair of radios and comparing the second differential timevalue to a second set of predetermined differential values associatedwith the second pair of radios.
 15. The method of claim 13, wherein thedetermining the location includes receiving a subset of potentiallocations determined by analyzing a first set of locations determined bycomparing the first differential time value to a first set ofpredetermined differential values associated with the first pair ofradios and a second set of locations determined by comparing the seconddifferential time value to a second set of predetermined differentialvalues associated with the second pair of radios.
 16. The method ofclaim 15, wherein the receiving the subset of potential locationsincludes receiving a union of the first set of locations and the secondset of locations.
 17. A system, comprising: at least one memory thatstores computer-executable instructions; and at least one processor,communicatively coupled to the at least one memory, that facilitatesexecution of the computer-executable instructions to at least: receive afirst observed time value associated with synchronization of radio linksbetween a first pair of radios of a wireless network and a userequipment of the wireless network, wherein the user equipment is in anidle-mode; and determine a first differential time value based on thefirst observed time value, a first reference observed time value, and afirst reference differential time value, wherein the first referenceobserved time value and first reference differential time value arepredetermined.
 18. The system of claim 17, wherein the firstdifferential time value is determined by subtracting the first referenceobserved time value from the first observed time value and adding thefirst reference differential time value.
 19. The system of claim 17,wherein the first observed time value is based, at least in part, on afirst propagation time for a first radio signal between a first radio ofthe first pair of radios and the user equipment, a second propagationtime for a second radio signal between a second radio of the first pairof radios and the user equipment, a first delay time associated with thefirst radio, and a second delay time associated with the second radio.20. The system of claim 17, wherein the at least one processor furtherfacilitates the execution of the computer-executable instructions todetermine a location for the user equipment based on the firstdifferential time value.